Decoupling Control of an Aviation Remote Sensing Stabilization Platform Based on a Cerebellar Model Articulation Controller

Abstract

To obtain high-resolution and high-precision images, the aviation remote sensing stabilization platform (ARSSP) is used, which enables the isolation of unpredictable aerial camera movements during aerial photography. However, because of the interaxle coupling interference and other nonlinear interferences in the ARSSP system, the imaging quality of the aerial camera is adversely affected. Therefore, we derived the dynamic model of moment coupling between shafts to illustrate the problem. On the basis of the former proportion integration differentiation (PID) controller based on cerebellar neural network, a nonlinear cross feedback decoupling scheme is adopted to reduce the adverse effects of these interferences. The cerebellar model articulation controller (CMAC) based on synovial membrane control (SMC) is used to reduce the nonlinear interferences caused by the new cross-decoupling module. To verify the effectiveness of the scheme, simulation, indoor and outdoor experiments were conducted. The results showed that the SMC-CMAC significantly reduced the interaxle coupling effect and effectively suppressed the nonlinear interference, resulting in a good tracking performance of the ARSSP system.

Keywords

• ARSSP
• nonlinear cross-feedback decoupling
• sliding-mode CMAC
• credit allocation
• optimization smoothness